The effects of washing a collagen sample prior to TEM examination

Transmission electron microscopy (TEM) is an important analysis technique to visualize (bio)macromolecules and their assemblies, including collagen fibers. Many protocols for TEM sample preparation of collagen involve one or more washing steps to remove excess salts from the dispersion that could hamper analysis when dried on a TEM grid. Such protocols are not standardized and washing times as well as washing solvents vary from procedure to procedure, with each research group typically having their own protocol. Here, we investigate the influence of washing with water, ethanol, but also methanol and 2-propanol, for both mineralized and unmineralized collagen samples via a protocol based on centrifugation. Washing with water maintains the hydrated collagen structure and the characteristic banding pattern can be clearly observed. Conversely, washing with ethanol results in dehydration of the fibrils, often leading to aggregation of the fibers and a less obvious banding pattern, already within 1 min of ethanol exposure. As we show, this process is fully reversible. Similar observations were made for methanol and propanol. Based on these results, a standardized washing protocol for collagenous samples is proposed.     

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

对空监视雷达探测威力检飞的几个问题

以新的观点论证了对空监视雷达探测威力检验飞行中所需的采样点数和飞行架次，讨论了预警机雷达威力检飞的特殊问题，包括地区选择、航线设计和目标机标定等。     

液压多功能小件落物打捞器的研制与应用

由于侧钻井、水平井特殊井身结构限制，常规的小件落物打捞器打捞成功率低。为此经过认真分析和现场实践，将常规机械操作的一把抓改成液压操作，常规强磁打捞器的圆柱形平面磁铁改成具有伸缩性的磁针，同时结合套铣筒，研制出一种液压多功能小件落物打捞器，克服了侧钻井、水平井井身结构的限制，大大提高了一次打捞成功率，现场应用效果明显。     

径向基函数神经网络的再学习算法及其应用

为了应用径向基函数神经网络逐步地识别待研究系统,文章针对径向基函数神经网络的再学习算法开展了深入的研究.应用严格的数学推理方法,将径向基函数神经网络的再学习问题转化为矩阵求逆的附加运算.详细给出了径向基函数神经网络再学习算法中增加新训练样本和增加新基函数的数学公式,同时对如何获取新的训练样本进行了研究.     

串行及并行A/D转换器在高速数据采集中的采样差别性分析

串行和并行接口模式是A/D转换器诸多分类中的一种,但却是应用中器件选择的一个重要指标.在同样的转换分辨率及转换速度的前提下,不同的接口方式不但影响了电路结构,更重要的是将在高速数据采集的过程中对采样周期产生较大影响.本文通过12位串行ADC ADS7822和并行ADC ADS774与AT89C51的接口电路,给出二者采样时间的差异性.     

水平井岩屑录井的影响因素及对策

由于岩屑沉积床的形成、井壁坍塌和井眼不规则、岩屑多次破碎、钻时资料失真及混油钻井液污染等因素影响，水平井的岩屑比普通直井更混杂、更细碎，代表性也更差，岩屑中的油气显示真假难辨。通过加密实测迟到时间，参考钻井参数及DC指数可以对岩屑进行较准确地分层、描述，采用多次荧光滴照、四氯化碳浸泡、气测资料分析等方法，能够有效地区分真假油气显示。     

切尔诺贝利事故释放的~(131)I所致牧草、奶类的污染水平及其变化规律

本文报道了苏联切尔诺贝利核电站事故释放的~(131)I对乌鲁木齐地区牧草、奶类的污染水平及动态变化规律。经估算,~(131)I经奶类所致成人(1.2μSv)和婴儿(120μSv)甲状腺最大待积剂量当量远低于我国放射卫生防护基本标准规定的年剂量限值,因此,对居民健康不会产生影响。     

四川南桠河一期工程姚河坝水电斜井开挖施工技术浅论

以姚河坝水电站引水隧洞50°倾角、长度为194.734m的斜井开挖为实例,从施工测量、开挖方法、通风防尘、临时支护斜井及安全施工等方面探讨长洞身、大倾角斜井在无爬罐条件下的人工开挖方法.